SLNE 耦合模型对 2010 年热浪预测能力的评估

IF 0.5 4区数学 Q4 MATHEMATICS, APPLIED

Russian Journal of Numerical Analysis and Mathematical Modelling Pub Date : 2024-08-07 DOI:10.1515/rnam-2024-0019

Rostislav Yu. Fadeev

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引用次数: 0

摘要

SLNE 是 2023 年开发的耦合模型。SL 和 NE 是 SLAV（基于绝对涡度方程的半拉格朗日）大气模型和 NEMO（欧洲海洋建模核心）海洋模型的前两个字母，这两个模型使用 OASIS3-MCT 软件进行耦合。SLAV 和 NEMO 的初始条件是根据俄罗斯水文中心的大气和海洋分析结果确定的。2010-2021 年后报精度研究表明，SLNE 在亚季节时间尺度上的误差与运行中的 SLAV 模型相当。与 SLAV 相比，SLNE 模式提高了对 2010 年热浪特征的预测能力，这是进一步改进耦合模式的动力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Evaluation of 2010 heatwave prediction skill by SLNE coupled model

SLNE is the coupled model, that was developed in 2023. SL and NE here are the first two letters from SLAV (Semi-Lagrangian, based on Absolute Vorticity equation) model of the atmosphere and NEMO (Nucleus for European Modelling of the Ocean) ocean model that have been coupled using OASIS3-MCT software. The initial conditions for SLAV and NEMO are specified from an atmospheric and ocean analyses produced in Hydrometcentre of Russia. The 2010–2021 hindcast accuracy study shows, that SLNE has comparable errors to the operational SLAV model on a sub-seasonal time scale. The SLNE model has improved prediction skill of the 2010 heatwave features in comparison to SLAV, that is a motivation for further work to improve the coupled model.

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来源期刊

Russian Journal of Numerical Analysis and Mathematical Modelling 数学-工程：综合

CiteScore

1.40

自引率

16.70%

发文量

审稿时长

>12 weeks

期刊介绍： The Russian Journal of Numerical Analysis and Mathematical Modelling, published bimonthly, provides English translations of selected new original Russian papers on the theoretical aspects of numerical analysis and the application of mathematical methods to simulation and modelling. The editorial board, consisting of the most prominent Russian scientists in numerical analysis and mathematical modelling, selects papers on the basis of their high scientific standard, innovative approach and topical interest. Topics: -numerical analysis- numerical linear algebra- finite element methods for PDEs- iterative methods- Monte-Carlo methods- mathematical modelling and numerical simulation in geophysical hydrodynamics, immunology and medicine, fluid mechanics and electrodynamics, geosciences.